Toward the end of my presentation at MRMW, there were three slides that seemed to have either resonated or ruffled feathers:
The three hypotheses:
- Information should be free. The marginal cost of collecting information is approaching zero. For a technologist, information is simply data. Data has storage costs and processing costs, but is not thought about in terms of acquisition costs. Nothing annoys an engineer more than suggesting that data should be purchased; we may pay for data for a time, if there are no other immediate solutions, but this becomes an engineering challenge: what do I need to build in order to collect that data on my own and convert this marginal cost into fixed cost?
- Insight is expensive. Conversely, turning data into something meaningful and insightful is valuable. That’s because that is the core of what engineers and technologists do: they find scalable and innovative ways to transform raw data into something brilliant.
- Action is priceless. Better yet is creating insights that lead directly to specific actions. This is of obvious value to the technologist, because it creates new data that can be used to build more advanced, real-time, responsive systems.
Shifting most of the perceived value into the “insight” and “action” categories doesn’t necessarily mean that that’s how the business model is written. For example, Google gives away enormous amounts of data, insights, and actionable services in exchange for equally enormous amounts of ad revenue. In games, “freemium” or “free to play” is another way of saying “give away the basic data, but charge for the good stuff.”
In a market research context:
- “Free data” = “do it yourself data.” Using Zoomerang or SurveyGizmo or Google Consumer Surveys may not be literally $0, but compared to the thousands of dollars previously spent on such projects it’s an insignificant difference.
- “Expensive insights” = “interpreted data.” The biggest issue with DIY research, of course, is that someone still needs to analyze the data and draw conclusions as to what it really means. Dropping survey data into a series of PowerPoint charts for each question isn’t insight, though — that’s just converting the data from one format to a different format. Distilling the data into a cohesive story uncovers insights.
- “Priceless action” = “consultative engagement.” When the vendor can deliver specific recommendations for the business, that is priceless. When the discussion at the end of a project engagement focuses on structuring the business problem and the best possible solutions (instead of “here is the data you asked for”), that is high value.
